Journals / Gazi Üniversitesi Fen Bilimleri Dergisi / 2004 / Cilt: 17 - Sayı: 1

LiBr-H2O eriyiğinin termodinamik özelliklerinin belirlenmesinde yeni bir model

A new model for determining the thermodynamic properties of LiBr-H2O solution

Pages
101–110
Publication Date
2022-10-18
DOI
—
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

In the study; in order to determine the hermodynamic properties of solution in all spans, a formulation was derived by a very well trained ANN model ($R^2$=l).

📌 3 Key Takeaways

🎯
Objective & Hypothesis:In this study, thermodynamic properties as enthalpy and entropy of LiBr-H2O solution were determined with The Artificial Neural Network (ANN) model for the absorption heat pump and cooling systems.
📊
Key Findings & Data:Data used in the model are based on empirical and experimental data available in the literature.
💡
Conclusion & Impact:In the study; in order to determine the hermodynamic properties of solution in all spans, a formulation was derived by a very well trained ANN model ($R^2$=l).
🔬Design:Modeling & Simulation
📍Scope:Comprehensive Sample
⚙️Variables:Domain Parameters

Abstract

In this study, thermodynamic properties as enthalpy and entropy of LiBr-H2O solution were determined with The Artificial Neural Network (ANN) model for the absorption heat pump and cooling systems. Data used in the model are based on empirical and experimental data available in the literature. It is not possible to determine the thermodynamic properties at each point with the experiments conducted in the limited working span. In the study; in order to determine the hermodynamic properties of solution in all spans, a formulation was derived by a very well trained ANN model ($R^2$=l).

Özet

Bu çalışmada, absorbsiyonlu ısı pompası ve soğutma sistemlerinde kullanılan LiBr-H2O eriyiğinin entalpi ve entropi gibi termodinamik özellikleri Yapay Sinir Ağlan (YSA) modeliyle belirlenmiştir. Bu modelde kullanılan veriler, literatürde mevcut olan ampirik ve deneysel veriler yardımıyla elde edilmiştir. Sınırlı çalışma aralıklarında yapılan deneylerle her noktadaki termodinamik özellikleri saptamak mümkün değildir. Çalışmada; çok iyi eğitilmiş bir YSA modeliyle ($^R2$=l), istenilen her aralıkta eriyiğin termodinamik özelliklerinin tespiti için bir formülasyon türetilmiştir.

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Cite This Article

YAKUT, A. K., ŞENCAN, A., DİKMEN, E. (2022). LiBr-H2O eriyiğinin termodinamik özelliklerinin belirlenmesinde yeni bir model. Gazi Üniversitesi Fen Bilimleri Dergisi, Cilt: 17 - Sayı: 1, 101–110. https://ajindex.com/articles/521726

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References (9)

  1. Chua, H.T., Toh, H.K., Malek, A., Ng, K.C., Sirinivasan, K., "A General Termodynamic Framework for Understanding the Behaviour of Absorption Chillers", Int. J. Refrig., 23:491-507 (2000)
  2. Herold, K.E., Radermacher, R., Klein, S.A., Absorption Chilles and Heat Pumps, CRC Press, New York: 324 (1996)
  3. Tozer, R.M., James, R.W.," Fundamental thermodynamics of ideal absorption cycles", Int. J. Refrig., 20(2): 120-135 (1997)
  4. Sun, D.W., "Thermodynamic Design Data and Optimum Design Maps for Absorption Refrigeration Systems", Applied Thermal Engineering, 17(3): 211-221 (1997)
  5. Chua, H.T., Toh, H.K., Malek, A., Ng, K.C., Sirinivasan, K., "Improved thermodynamic property fields of LiBr-H2O solution", Int. J. Refrig., 23: 412-429 (2000)
  6. Fu, L.M., Neural Networks in Computer Intelligence, Mc Graw-Hill International Editions: 460 (1994)
  7. Tsoukalas, L.H., Uhrig, R.E., Fuzzy and Neural Approaches In Engineering, John Wiley & Sons Inc.: 587 (1997)
  8. Efe, Ö., Kaynak, O., Yapay Sinir Ağları ve Uygulamaları, Boğaziçi Üniversitesi, İstanbul (2000)
  9. Kalogirou, S.A, "Applications of artificial neural networks in energy systems A review", Energy Conversion & Management,40: 1073-1087 (1999).